D Eng ThesisThe spiral jet mill is a widely applied and robust apparatus for reduction of mean particle size to less than 10 microns. Despite the spiral jet mill being a well established technology, there are no proven scale up methodologies and many commercial mill designs are not optimised for energy efficiency.
Within this thesis a novel analytical derivation is presented for spiral jet mill cut size as a function of micronisation settings, gas thermodynamic properties and empirically derived constants for the material and mill. The derivation is corroborated by experimental evidence for a number of products owned by GlaxoSmithKline (GSK) and previously reported data in the academic literature. This equation provides an insight into the interaction between aerodynamic particle classification and fine grinding for the spiral jet mill, and brings great advancement to the level of understanding in the academic literature on the control of particle size with a spiral jet mill. The constants within the equation can be determined empirically for a given material and mill, leading to a better prediction across a design space than standard empirical models. A scale up methodology is proposed for a high value material by using a small scale mill to determine the material specific constants of the high value material and a cheaper surrogate material to determine mill specific parameters at increased scale.
In addition to a novel analytical derivation, this thesis presents the first ever Computational Fluid Dynamics (CFD) based optimisation of a combined spiral jet mill and cyclone. Some combined spiral jet mill and cyclone designs have poor cyclonic separation yields, and this thesis presents the CFD and experimental investigation which led to an optimised mill and cyclone that significantly improved yield while maintaining similarity of particle size
